PMID: 16617613Apr 19, 2006Paper

Using generalized additive models for construction of nonlinear classifiers in computer-aided diagnosis systems

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
María J LadoPablo G Tahoces

Abstract

Several investigators have pointed out the possibility of using computer-aided diagnosis (CAD) schemes, as second readers, to help radiologists in the interpretation of images. One of the most important aspects to be considered when the diagnostic imaging systems are analyzed is the evaluation of their diagnostic performance. To perform this task, receiver operating characteristic curves are the method of choice. An important step in nearly all CAD systems is the reduction of false positives, as well as the classification of lesions, using different algorithms, such as neural networks or feature analysis, and several statistical methods. A statistical model more often employed is linear discriminant analysis (LDA). However, LDA implies several limitations in the type of variables that it can analyze. In this work, we have developed a novel approach, based on generalized additive models (GAMs), as an alternative to LDA, which can deal with a broad variety of variables, improving the results produced by using the LDA model. As an application, we have used GAM techniques for reducing the number of false detections in a computerized method to detect clustered microcalcifications, and we have compared this with the results obtained ...Continue Reading

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Citations

Sep 30, 2008·The International Journal of Cardiovascular Imaging·Anja J ReimannMartin Heuschmid
Sep 25, 2010·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Nan-Chyuan TsaiSheng-Liang Hsu

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